Feature image Is MongoDB a NoSQL database?

Is MongoDB a NoSQL database?

By Laurent Mauer · November 4, 2022 · 6 min read

Yes, MongoDB is a NoSQL database. MongoDB is an open-source NoSQL database. MongoDB is a document-oriented database. Moreover, MongoDB is one of the famous NoSQL databases. NoSQL is one of the favorite types of non-relational databases. It is best for processing structured, semi-structured, and unstructured data.

What is MongoDB?

MongoDB is one of the open-source database management systems (DBMS). It uses a document-oriented database model. Most of the MongoDB is written in C++. More importantly, MongoDB is capable of supporting various kinds of data. MongoDB also stores the data in flat files with the help of using binary storage objects. Data storage is compact and efficient for higher volumes. Moreover, data is stored in JSON-like documents in MongoDB. As a result, the database becomes flexible and scalable.

MongoDB is based on a document-oriented database model. Every MongoDB database comprises different collections that contain more documents. Each document becomes different based on a varying number of fields. Each varying document model will vary based on size and content. Their data model features help to store arrays and other complex structures in hierarchical order.

What is NoSQL?

NoSQL is the newest database management system that fundamentally differs from relational database systems. It is an efficient, highly scalable, and flexible database management system. NoSQL is suitable for storing as well as processing unstructured and semi-structured data. Even though this feature is not possible in RDMS tools. NoSQL is the simple approach to database design that best accommodates the multiple database models that include columnar, key-value, and graph formats. The data consists of the NoSQL system at a lower level than in SQL databases. NoSQL databases prove to provide high scalability performance. NoSQL system consists of architecture that operates at very high speeds and sufficient flexibility at the developer end.

Has MongoDB replaced NoSQL?

We have many limitations with Relational Databases for processing and storing a sufficiently large volume of social media posts. NoSQL appears as the rescue for Big data. You can program in a NoSQL database to improve its efficiency. There are four types of NoSQL databases. NoSQL is best in terms of handling large-volume data. You won’t find any NoSQL databases to be schema-free or completely relaxed schemas. Moreover, MongoDB possesses an excellent feature for processing data. For the aggregation purpose, we use Map reduce model.

A MapReduce is one of the programming models that comprises two essential features: Map () and Reduce (). Usually, the Map () feature is employed to perform filtering and sorting tasks, while Reduce () is used to perform a summary operation. In addition, MongoDB consists of the excellency feature of running over multiple servers. Every data is duplicated to keep the system up and running successfully in case hardware failure occurs. MongoDB is an entirely schema-free database.

Along with this, its architecture consists of documents in a single file. As the collection is schema-less, it comprises various content, fields, and size compared with all the other documents in the same group. Most of the features of NoSQL are connected with multiple offerings of MongoDB. Thus, neither NoSQL can replace MongoDB nor MongoDB can return NoSQL.

Key Characteristics of MongoDB

Here we have mentioned some of the exciting characteristics of MongoDB:

  • High Performance

MongoDB is the best open-source database with excellent performance. It has a high tendency in terms of scalability and availability of the database. It also supports rapid query response with the help of its feature of indexing and replication.

  • File Storage

We can use MongoDB as a file system with a load-balancing feature and data replication on different machines for storing files.

  • Replication

With this feature, data can be easily distributed over multiple nodes. It comprises primary as well as secondary nodes for the replication of data. This replication is done with the help of master-slave architecture.

  • Sharding

This process allows the data to be distributed across multiple physical partitions known as shards. It happens with the MongoDB automatic load-balancing process. We use this feature whenever we need to tackle large datasets.

Key Characteristics of NoSQL

Here we mentioned some of the exciting characteristics of NoSQL:

  • Multi-model

This feature is excellent for making the NoSQL database much more flexible whenever it comes to the point of handling data.

  • Scalability

Regarding NoSQL scalability, the NoSQL databases are highly scalable to cope with the high volumes of data and any complexities in cloud applications. This scalability feature improves the overall performance, allowing high-speed readability too.

  • Flexibility

With this feature, NoSQL databases can process large varieties of data. It can even process structured, unstructured, and semi-structured data. It works well in most processors. Moreover, it allows storing databases on any number of processors and thus can enhance its performance.

  • Minimum Downtime

NoSQL is elastic, allowing its workload to spread to various servers automatically.

Critical differences between MongoDB and NoSQL

Firstly, the MongoDB database is a top-level container consisting of one or more collections. In contrast, the NoSQL database stores top-level namespaces and containers for storing data.

MongoDB is wholly based on a document store data model where the data is stored in the BSON format. BSON format is nothing but a binary JSON format. NoSQL is one of the open-source documented databases that have the excellent feature of scalability and data modeling along with the capability of data management of large data sets in developing enterprise applications.

MongoDB consists of advanced features for searching any field or query, whereas NoSQL databases are best for data storage and flexibility.

MongoDB also possesses the feature of sharding for scaling horizontally. Similarly, the NoSQL system helps to drag and drop your data into a folder. After it generates query for creating multiple entity relational model

Conclusion

At RestApp, we’re building a Data Activation Platform for modern data teams with our large built-in library of connectors to databases, including MongoDB, data warehouses and business apps.

We have designed our next-gen data modeling editor to be intuitive and easy to use.

If you’re interested in starting with connecting all your favorite tools, check out the RestApp website or try it for free with a sample dataset.

Discover the next-gen end-to-end data pipeline platform with our built-in No Code SQL, Python and NoSQL functions. Data modeling has never been easier and safer thanks to the No Code revolution, so you can simply create your data pipelines with drag-and-drop functions and stop wasting your time by coding what can now be done in minutes! 

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Laurent Mauer
Laurent Mauer
Laurent is the head of engineer at RestApp. He is a multi-disciplinary engineer with experience across many industries, technologies and responsibilities. Laurent is at the heart of our data platform.

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